Modeling of lithium-ion battery for energy storage system simulation

Battery models for simulation are useful for estimating operating life, stability, and related characteristics of batteries used in circuits and systems. This report presents a dynamic model of lithium-ion battery. The model accounts for nonlinear equilibrium potentials, rate- and temperature-dependencies, thermal effects and responses to transient power demand. In this project, the author developed a lithium-ion battery model from the mathematical equations given in a research paper [I]. Simulation using SIMPLORER software was performed. The charge and discharge characteristics of the model were obtained and the results were compared to a battery manufacturer’s data of a Sony US 18650 lithium-ion battery cell and the experimental data of an UltraLife UBBL10 Lithium-ion battery system. Simulation results of the lithium battery model agreed well with the manufacturer’s data in all the static characteristics. The model can be easily modified to fit parameters from different batteries and can be extended for wide dynamic ranges of different temperatures and current rates. The model also can be used in parallel and in series. The simulation results are nearly the same as experimental data.Master of Science (Power Engineering

Smart energy management system for microgrid planning and operation

A smart grid refers to an electricity transmission and distribution system that incorporates elements of traditional and cutting-edge power engineering, information technology, and communications, which can provide better grid performance and to support a wide array of additional custom services to consumers. A smart grid would facilitate the full use of sustainable energy technologies like solar power, wind power and fuel cells with the help of distributed energy storage systems (ESS). To understand the behavior of a smart grid, the author develops models suitable for overall analysis and design. The final goal is to lay the groundwork which would allow efficient management of the smart grid by solving all kinds of optimization problems, i.e., minimizing the operating costs, enhancing efficiency and reducing emission level while meeting the load demand. Smart Energy Management System (SEMS) is a core part for a smart grid system, which can make this system more intelligent. The optimal placement of the capacitors with the renewable energy is also discussed in this thesis. To handle the multi-objective optimization in the smart grid, a Jump and Shift method is proposed in this thesis. It aims to solve a large scale linear/nonlinear programming problem where the constraints are related to another large scale linear/nonlinear programming. A 14-bus and 112-bus power systems are tested to verify the multi-objective optimization algorithm based on the Jump and Shift method. ESS plays an important role in the smart grid. It is desirable to shave the peak demand and store the surplus electrical/renewable energy. A new method based on the cost-benefit analysis for the optimal sizing of an ESS in a microgrid (MG) is proposed. The Unit Commitment problem with the required spinning reserve capacity for the MG is considered in this method. To deal with the optimal control of ESS, the author presents an online management energy system for the lithium-ion (Li-ion) battery based on the proposed mathematical battery model and the adaptive Extended Kalman Filter (EKF) method. The proposed technique can be used to predict the state of charge (SOC) of the Li-ion battery via the online measured voltage and current.DOCTOR OF PHILOSOPHY (EEE

Decentralized state estimation for hybrid AC/DC microgrids

This paper presents a decentralized state estimation (SE) for the newly emerging hybrid ac/dc microgrid. The microgrid consists of an ac and a dc network which are connected via the interlinking ac/dc converter. The proposed SE is able to estimate the state variables of both networks in a decentralized way that the estimation is separately conducted while only limited information is exchanged during the process. The dual decomposition approach is adopted as the decentralized technique in this paper. Simulation results suggest that the proposed decentralized SE performs comparably to the centralized SE for the hybrid ac/dc microgrids in terms of accuracy, convergence, and robustness

Demand response program in Singapore’s wholesale electricity market

Singapore is going to implement a demand response (DR) program to further enhance the efficiency and competitiveness of its electricity market. This paper aims to provide an in-depth investigation of this DR program which features demand side bidding and incentive payments. First, the current market clearing model (MCM) of Singapore’s existing wholesale market, which has no demand side bidding, is introduced. A mathematical model of the MCM is formulated to explain and solve the current market clearing process, where the energy and ancillary services are settled simultaneously through a form of auction pricing. Second, the mechanism of how the demand side bidding is incorporated into the current MCM is explained, with an emphasis on the demand side offer and the newly introduced constraints. A modified MCM with DR is then formulated. Third, the incentive payment mechanism intended to promote DR participation is elaborated. Numerical analysis is performed to demonstrate how the current MCM and MCM with DR work, as well as how the incentive payment is settled. Various numerical case studies are carried out to discuss the economic benefits from participating in the DR program.Accepted versio